Epidemiologic research on communicable diseases has evolved from using static models suitable for noncommunicable diseases to using dynamic mathematical models more appropriate for studying the diffusion of infections through populations over time. With the application of deterministic and stochastic models, attention has shifted from analyzing only the risk factors of individuals, to also the interactions between individuals that drive transmission of infection. For sexually transmitted infections (STIs), the focus of research has thus shifted from an initial emphasis on individual sexual risk behaviors to a more comprehensive integration of data including sexual mixing matrices, partnership concurrency, other sex partnership characteristics and ecological factors that influence all of these levels of interaction. Surprisingly little empirical data have been collected on these higher order patterns of sexual interaction, particularly on potential differences in patterns associated with the various STIs that have very different natural histories. The integrated training activities and research proposed will provide Dr. Golden with skills to facilitate his goal of becoming an independent academic investigator as he collects and analyzes such data. The proposed studies include systematic, concurrent analyses of patterns of sexual mixing and sexual network characteristics for important STIs with very dissimilar natural histories: two bacterial STIs (gonorrhea and chlamydial infection) and two viral STIs (newly acquired genital herpes and HIV). Three federally funded studies at the UW already support recruitment of individuals with these infections, allowing the proposed studies to be added with only small additional cost. Mentoring by Dr. Geoff Garnett at Oxford University, and Drs. King Holmes and Martina Morris at the UW will help guide development of data on sexual networks and the use of such data to improve mathematical models designed to assess the potential impact of innovative preventive interventions. Specific aims will be to: 1) define sexual networks associated with gonorrhea and chlamydial infection and use empiric network data in mathematical models of transmission dynamics to evaluate the potential effect of partner notification, counseling and treatment on the prevalence of these two infections; and 2) To define the sexual networks associated with the acquisition of HIV and genital HSV infections, compare them to sexual networks of people with bacterial STI and without STIs, and use empiric network data in mathematical models of transmission dynamics to evaluate the potential effects of behavior and antiviral treatment interventions on the prevalence of these infections.